Mechanism for Facilitating Dynamic Phase Detection With High Jitter Tolerance for Images of Media Streams

ABSTRACT

A mechanism for facilitating dynamic phase detection with high jitter tolerance for images of media streams is described. In one embodiment, a method includes calculating stability optimization of an image of a media stream based on a plurality of pixels of two or more consecutive frames relating to a plurality of phases of the image, calculating sharpness optimization of the image, and selecting a best phase of the plurality of phases based on the stability and sharpness optimization of the image. The best phase may represent the image such that the image is displayed in a manner in accordance with human vision perceptions.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/115,324, filed Nov. 1, 2013, which is a national stage application ofPCT Patent Application No. PCT/CN2013/070826, filed Jan. 22, 2013, bothof which are incorporated by reference in their entirety.

FIELD

Embodiments of the invention generally relate to media communicationand, more particularly, to a mechanism for facilitating dynamic phasedetection with high jitter tolerance for images of media streams.

BACKGROUND

With digitization of electronic devices, such as increasing number oftelevisions having High-Definition Multimedia Interface (HDMI) andMobile High-Definition Link (MHL) connectors, it is common to convertanalog signals to digital signals to remove analog connectors andimprove picture quality. However, such computer-generated images arelow-quality and unintelligent as they do not take into account anynumber of critical factors.

SUMMARY

A mechanism for facilitating dynamic phase detection with high jittertolerance for images of media streams is described.

In one embodiment, a method includes calculating stability optimizationof an image of a media stream based on a plurality of pixels of two ormore consecutive frames relating to a plurality of phases of the image,calculating sharpness optimization of the image, and selecting a bestphase of the plurality of phases based on the stability and sharpnessoptimization of the image. The best phase may represent the image suchthat the image is displayed in a manner in accordance with human visionperceptions.

In another embodiment, an apparatus performs a method according to anyone or more of the operations mentioned above.

In another embodiment, a system includes one or more devices performinga method according to any one or more of the operations mentioned above.

In yet another embodiment, at least one machine-readable mediumcomprising a plurality of instructions that in response to beingexecuted on a computing device, causes the computing device to carry outa method according to any one or more of the operations mentioned above.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the invention are illustrated by way of example, and notby way of limitation, in the figures of the accompanying drawings inwhich like reference numerals refer to similar elements:

FIG. 1 illustrates a media device employing a dynamic phase detectionmechanism according to one embodiment;

FIG. 2A illustrates dynamic phase detection mechanism according to oneembodiment;

FIG. 2B illustrates an image pattern of an image selected for dynamicphase detection according to one embodiment;

FIG. 2C illustrates dynamic phase detection according to one embodiment;

FIG. 3 illustrates a method for dynamic phase detection according to oneembodiment; and

FIG. 4 illustrates a computing device capable of employing one or moreembodiments.

DETAILED DESCRIPTION

Embodiments of the invention are directed to facilitating automaticphase detection with high jitter tolerance for images of media streams.

FIG. 1 illustrates a media device employing a dynamic phase detectionmechanism 110 according to one embodiment. Communication or networkmedia device 100 may include any number and type of media devices, suchas a source device (e.g., a transmitter), a sink device (e.g., areceiver), an intermediate device (e.g., an analog-digital convertor),an amplifier, etc. Communication media device 100 may include any numberof components and/or modules that may be common to a variety of mediadevices (such as a sink device, a source device, etc.); however,throughout this document and particularly with reference to FIG. 2, inone embodiment and for brevity, clarity and ease of understanding,communication media device 100 may include and be referred to as a hostdevice or host machine employing dynamic phase detection mechanism(“phase mechanism”) 110 and set to be in communication with any numberand type of devices, such as one or more source devices and/or sinkdevice and/or intermediate devices over a network (e.g., a broadcastingnetwork, such a cable or satellite broadcasting network, a Wide AreaNetwork (WAN), a Local Area Network (LAN), a Personal Area Network(PAN), a Metropolitan Area Network (MAN), a cloud-based network, anintranet, the Internet, etc.).

A source device refers to a transmitter or a transmitting device that isresponsible for transmitting data (e.g., media audio and/or videodata/content streams) to a sink device that refers to a receiver or areceiving device responsible for receiving the transmitted data over acommunication network. Examples of a source device may include consumerelectronics devices, such as a personal computer (“PC”), a mobilecomputing device (e.g., a tablet computer, a smartphone, etc.), an MP3player, an audio equipment, a television, a radio, a Global PositioningSystem (“GPS”) or navigation device, a digital camera, an audio/videorecorder, a Blu-Ray player, a Digital Versatile Disk (“DVD”) player, aCompact Disk (“CD”) player, a Video Cassette Recorder (“VCR”), acamcorder, etc. Examples of a source device may further include acomputing device, a data terminal, a machine (e.g., a facsimile machine,a telephone, etc.), a video camera, a broadcasting station (e.g., atelevision or radio station, a cable headend, etc.), a cablebroadcasting head-end, a set-top box, a satellite, etc. A sink devicemay include one or more of the same examples of media devices as thoselisted for the source device. Similarly, an intermediate device mayinclude one or more of the same media device as those listed for thesource device or it may include a specialized convertor device tofacilitate conversion of the media from one form to another, such asfrom analog to digital or vice versa.

Communication media device 100 may include an operating system 106serving as an interface between any hardware or physical resources ofthe source device 100 and a sink device or a user. Communication mediadevice 100 may further include one or more processors 102, memorydevices 104, network devices, drivers, or the like, as well asinput/output (“I/O”) sources 108, such as a touchscreen, a touch panel,a touch pad, a virtual or regular keyboard, a virtual or regular mouse,etc.

Embodiments provide phase mechanism 110 to facilitate an internalphase-locked loop or phase lock loop (PLL) to dynamically generate atarget pixel clock for analog to digital conversion (ADC) and using thepixel clock to search for a phase that can be used to generate imagesthat are of quality that is preferred by the human eye. The phasedetection process by phase mechanism 110 may be referred to as autophase detection or automatic phase detection (APD) or APD processthroughout this document. However, it is to be contemplated that the useof the term “APD” or any of the aforementioned corresponding termsshould not be read to limit embodiments to device, hardware, software,etc., that carry that label in products or in literature external tothis document.

For example, conventional mechanism provide image ‘qualities that arecomputer-guessed because they do not take into consideration the workingor preference of the human eye, such as what qualities or factors, suchas the level of sharpness or the amount of stability, etc., might appealto humans (also referred to as “users”, “end-users”, “viewers”, etc.).It is contemplated that different phase configuration results indifferent display quality, such as at good phases, displays are clearand sharp, while at bad phases, displays are blurry and dark. Similarly,some phases may have significant noise such as horizontal flashingstripes which may be visually annoying to users. Phase performances mayvary according to their source, platform, format, etc., and therefore,identify the best performing phase is cumbersome, particularly in acomplex media environment. Embodiments provide a comprehensive solutionthat is accurate, cost-efficient, resource-efficient, fast, relativelysimple, and having strong jitter tolerance, etc. The solution, in oneembodiment, is based on the known information about human visionperceptions and using that information, which can be obtained from anynumber of reports put forth by the scientific and medical community, amore appropriate phase is determined and chosen so that resulting imagequality is pleasing to the human eye and is regarded as high quality byusers (such as in terms of its sharpness, stability, pixel distribution,etc.).

As will be further described with reference to FIG. 2A, once the APDprocess has started by phase mechanism 110, it moves phase position fora start position to an end position with a defined increment for eachprocess within the larger process. In one embodiment, at each phase ofthe image, various factors (e.g., stability optimization, sharpnessoptimization, image consistency evaluation, image suitabilityevaluation, etc.) are calculated and/or determined evaluate the imagesuitability and/or quality that reflects, for example, display sharpnessand stability. The collected information may then be compared across allphase locations and eventually a phase with the best characteristics ischosen. As aforementioned, in one embodiment, the best characteristicsmay be based on the well-known science of how the human vision perceivesimage qualities so that the selected phase facilitates the best imagequality in terms of what a typical human eye would appreciate and enjoy.Further, to make the comparison fair so that an apple-to-applecomparison is pursued, as a pre-requisite, APD's input image, duringdetection time, may be made still and consistent and may have the imagecontain a certain amount of contrast to sufficiently stimulate phaseperformance functions.

Phase mechanism 110 may be triggered and used in an automatic mode or amanual mode where, for example, raw data relating to each phase locationmay be determined or calculated by various components, while results ofsuch calculations may be provided by other components of phase mechanism110 by maintaining a handshake between these components. In case of theautomatic mode, to preserve system resources and achieve fast completionof the process, certain components may perform multiple functions, suchas calculating both the raw data and sort phase candidates withoutinvolving other components. Furthermore, for debugging and/orpost-process purposes, at both automatic and manual modes, raw datacalculated relating to each phase candidate may be stored in a memorywhich may be accessed after the APD process is completed. Similarly,once APD is performed, the circuit may be turned off and the phase maystay as hardware or software select till the next APD process istriggered.

FIG. 2A illustrates dynamic phase detection mechanism 110 according toone embodiment. In one embodiment, phase mechanism 110 includes a numberof components, such as input image scanner (“scanner”) 202, stabilityoptimization logic (“stability logic”) 204 having pixel intensity module(“pixel module”) 206 and frame intensity module (“frame module”) 208,sharpness optimization logic (“sharpness logic”) 210 having sharpnessfunction module (“sharpness module”) 212, image consistency evaluationlogic (“consistency logic”) 214 having energy function module (“energymodule”) 216, image suitability logic (“suitability logic”) 218,handshake logic 220, communication components 222, and compatibilitymodule 224. Throughout this document, various components 202-224 ofphase mechanism 110 may be interchangeably referred to as “logic”,“processing logic”, or “module” and may include, by way of example,software, hardware, and/or any combination of software and hardware,such as firmware.

In one embodiment, scanner 202 may be used to scan the incoming images.Although embodiments are not limited to any particular image or type ofimage, certain conditions or criteria may be predetermined and appliedfor performing, for example, a more efficient processing for phaseselection. For example, for a better apple-to-apple APD, a still imagemay be selected for phase examination. Further, a still image may bepredetermined to contain some contrast, such as the selected image maynot be a blank image or a solid-colored screened imaged or a grey-scaledimage, etc. For example, as illustrated in FIG. 2B, an exemplary image230 having repetitive vertical black and white lines ofsingle-pixel-width may be regarded as an image with the best pattern tobe selected to differentiate phase quality using phase mechanism 110.

In one embodiment, stability logic 204 facilitates determination andcalculation of stability of the selected image, such as image 230 ofFIG. 2B. For example, stability or stability function may be describedas the statistic characterization of dot-to-dot difference betweenconsecutive frames of the image on the same phase for each phase of theimage. The more pixels are involved, the higher the accuracy isexpected. It is contemplated that for an ideal solution, all dots for atleast two consecutive frames may be compared and although such task maybe performed using phase mechanism 110, for cost and time efficiencypurposes, a small portion of dots with limited memory requirement may beselected for comparison purposes. As will be further described withreference to FIG. 2C, pixel intensity may be calculated using pixelmodule 206 and frame intensity may be calculated using frame module 208to determine the stability function of the selected image.

Referring now to FIG. 2C, a number of M×N pixels or pixel points of twoconsecutive frames 232, 234 of the selected image, such as image 230 ofFIG. 2B, may be compared. For brevity and ease of understanding, frame232 is considered frame 0 of phase k, while frame 234 is frame 1 of thesame phase k. is contemplated there may be 32 phases, such as rangingfrom k=0 thru k=31. For both frames 232, 234, a grid with dimension M×Nmay be defined having M pixels selected per line and N lines selectedper frame. For each horizontally selected line, M pixels may be equallydistributed, while for each vertically selected row, N pixels may beequally distributed. Both the horizontal direction and the verticaldirection may be configurable, while randomness may be added, so thatrandomly selected M×N pixels may be used to statistically represent thewhole frame 232, 234.

In the illustrated embodiment, 1024 pixels are chosen as the base (e.g.,M×N=1024), where M and N are selectable as 2̂X, X in a range of 0 to 10.Randomness may be achieved by, for example, two fixed Linear FeedbackShift Registers (LFSR), where one for horizontal randomness generation,for M pixels per line, and the other for vertical randomness generation,for N lines per picture. Their seeds are random (e.g., randomness may betied to machine time), but for each APD calculation, identical seeds orpixels 242, 244, 252, 254, 262, 264, 272, 274-may be selected for phasecandidates. The seeds may be needed at the start of each frame and onceLFSR is loaded with the seeds, they may operate as defined by thepolynomials. Further, it is to be noted that for pixels 242, 244, 252,254, 262, 264, 272 and 274, but that their locations may be fixed foreach APD calculation. When randomness is applied, certain locationvariation may be placed on top of the fixed M×N grid. The locationvariation may be pseudo-random and mathematically predictable due topre-defined polynomial and seeds, which may make the selected pixels'locations 242, 244, 252, 254, 262, 264, 272, 274 repeatable from frame232 to frame 234. This way frame statistics relating, to frames 232 and234 may be obtained, but without having to incur any frame buffer cost.

Once M×N random grid is decided, their individual intensity differencemay be collected and overall intensity variation may be characterizedfrom the initial phase location (e.g., phase k=0) to the ending phaselocation (e.g., phase k=31). It is contemplated that the better thephase in terms of the PLL jitter tolerance performance, the lower theoverall intensity difference as calculated by pixel module 206 and framemodule 208 that is then used to calculate stability optimization asprovided by stability logic 204.

For example, pixel (0,0) 242 of frame 232 may be selected and comparedto its counterpart pixel (0,0) 244 of frame 234 so the pixel intensitydifference (AbsDiff(0,0)) 246 for pixels 242, 246 may be calculatedusing pixel module 206 using, for example, the following equation:AbsDiff(i,j,k)=|P(i,j,k,0)−P(i,j,k,1)|, 0≦i<n, 0≦j<m, 0≦k<32. Similarly,the aforementioned equation may be used by pixel module 206 to calculatepixel intensity differences AbsDiff(n−1,0) 256, AbsDiff(0,m−1) 266,AbsDiff(n−1,m−1) 276 for other corresponding pixels 252, 254, 262, 264,272, 274. Once the pixel intensity differences 246, 256, 266, 276 havebeen calculated, frame module 208 may be used to calculate the frameintensity difference (AbsDiffTotal(k)) using, for example, the followingequation:

${{{AbsDiffTotal}(k)} = {\sum\limits_{i = 0}^{n - 1}{\sum\limits_{j = 0}^{m - 1}{{AbsDiff}\left( {i,j,k} \right)}}}},{0 \leq k < 32.}$

Once the frame intensity difference have been calculated, stabilitylogic 204 may then use the frame intensity difference calculation togenerate the stability optimization for each phase using, for example,the following equation: Minimize(AbsDiffTotal(k)), 0≦k<32. Further,based on the criteria set forth by the aforementioned equations, thevarious phase candidates may be internally sorted out so that the bestphase may be selected. This emulation platform demonstrates theeffectiveness of stability optimization of phases and it is contemplatedthat for images with large amounts of pixel-to-pixel transitions, astronger jitter tolerance may be achieved by phase mechanism 110.

In one embodiment, since clock and phase may be highly relevant to highfrequency signals and not so relevant to low frequency signals,sharpness optimization may be generated using sharpness logic 210. Forexample and in some embodiments, sharpness logic 210 may use highfrequency component energy (HFCE) to calculate sharpness optimization ofphases. The following equation defines HFCE and may be used by sharpnessfunction module 212 to obtain a sharpness function (HFCE(k)) for anynumber of phase candidates:

if  (−p_(i, j − 1)^(′) + 2^(*)p_(i, j)^(′) − p_(i, j + 1)^(′) > hf_threshold)hfce_(i, j) = −p_(i, j − 1)^(′) + 2^(*)p_(i, j)^(′) − p_(i, j + 1)^(′);

Once the sharpness function is obtained, sharpness optimization logic210 may use the available sharpness function to calculate sharpnessoptimization for various phases candidates using, for example, thefollowing equation: Maximize(HFCE(k)), 0≦k<32. Where i and j representline counter and column counter, respectively, for H×V image resolution.P_(i,j) represents a pixel value, while hf_threshold represents aprogrammable register setting. Based on the criteria set forth by theaforementioned equations, the phase candidates are internally sortedout, while an image with fast pixel-to-pixel transition may generate ahigher HFCE than the image with slow transition.

Further, if, due to asymmetric sharpness distribution across multiplephase candidates, the sharpest phase with the maximum HFCE is not thecleanest one (e.g., contains low-level, but noticeable noise that canmakes display not as quiet as expected), a cleaning process may beperformed after the phase sorting to make ensure that the selected phasecandidate falls into a relatively quiet neighborhood. This may representa trade-off in-between image sharpness and neighborhood consistency.

Based on APD optimization criteria, to sweep through all phasecandidates, it may take approximately one second for the calculationprocess to conclude. However, during this calculation, the selectedimage may change abruptly and APD's assumption relating to a still imagemay also be in danger of changing. To avoid or fix such cases, imageconsistency of the image is monitored using consistency logic 214, basedon energy function determined by energy module 216, during the phasedetection process. The base energy function may be calculated orapproximated by the sum pixel values using energy module 216 and, forexample, the following equation:

${{afce} = {\sum\limits_{i}{\sum\limits_{j}P_{i,j}}}},$

where afce stands for All Frequency Component Energy (AFCE), i and jrepresent line counter and column counter, respectively. In general, foreach APD calculation, if the input image remains still, the distributionrange of AFCE may be relatively small. If, for example, the distributionis too wide compared to a particular threshold (e.g., a predefinedthreshold), it would imply an abrupt input image change and thus theimage may be deemed inconsistent. The distribution may be normalized andmeasured by, for example, the following equation:[Max(AFCE)−Min(AFCE)]/Max(AFCE), where Max(AFCE) and Min(AFCE) stand formaximum AFCE and minimum AFCE, respectively during the same APDcalculation. Further, using consistency logic 214, the threshold may becontrolled by a register (e.g., reg_csst_thresh[1:0]), while theconsistency may be reflected by a register bit (e.g., reg_apd_img_csst).

In one embodiment, image suitability logic 218 may be used to examinethe edge intensiveness of the selected image. If the number of edges isequal to or more than a particular (e.g., predefined) threshold, theimage may be deemed suitable; in contrast, if the number of edges isless than the threshold, the image may be determined as unsuitable.Using suitability logic 218, the threshold may be controlled by aregister (e.g., reg_edg_thresh[1:0]), while the suitability may bereflected by a register bit (e.g., reg_apd_img_suitable).

Based on the condition that the image is still (as determined from imageconsistency evaluation as obtained by image consistency logic 214) andsuitable (as determined from image suitability evaluation as obtained byimage suitability logic 218) for phase detection, the best phasecandidates is decided by both sharpness optimization (as obtained usingsharpness optimization logic 210) and stability optimization (asobtained using stability optimization logic 204). In one embodiment, thebest phase is selected as it may correspond to the highest levels ofstability and the sharpness.

In one embodiment, in case of any conflict between the stability and thesharpness, if the image under testing has a large amount ofpixel-to-pixel transitions and is jitter-sensitive (e.g., gray_(—)11pattern), stability optimization of the phase may be favored oversharpness optimization to ensure jitter tolerance which may be regardedas more important than other factors. In contrast, for images with fewerpixel-to-pixel transitions or those that are less sensitive to jitter,sharpness optimization may be preferred and applied. In other words, anideal phase would be the one with best stability and sharpness levelsthat is strong in jitter tolerance so the best possible image may beprovided to the user, but in cases where the APD process may have tonegotiate between stability and sharpness, the best selected phase maycorrespond to the an image that is selected from the best neighborhoodof images (as may be seen on a graph) that provides the strongestcorrelation with the known human vision perspectives.

Furthermore, in one embodiment, handshake logic 220 may be used tofacilitate a handshake between various processes or components of phasemechanism 110. For example, an interrupt associated with a current phasemay be generated here, while various components of phase mechanism 100may collect the relevant data and once the process is completed, theinterrupt will be cleared and the state may transition to anotherprocess.

Communication components 222 may be used to facilitate communicationbetween various media devices, such as source devices, sink devices,intermediate devices/analog-digital convertors, etc., of differentbands, makes, versions, mechanisms, etc. Communication components 222further provide various modules to facilitate communication betweenvarious components 202-224 of phase mechanism 110 as well as with andthrough certain default communication components (such as receivers,transmitters, analog-digital convertors, audio-video convertors,processors, loud speakers, I/O components, buffers, and the like) thatmay be part of various media devices. Similarly, compatibility module224 facilitates compatibility between media devices, such as sourcedevices, sink devices, intermediate devices/analog-digital convertors,etc., of different bands, makes, versions, mechanisms, etc., and is notlimited to any particular number or type of media devices, technology,components, standards, audio/video formats, audio and video signaltypes, hardware, connections, software, equipment, such as displays,wires, connections, etc., or the like. It is to be noted and appreciatedthat any reference to “television” or other similar media devices ismade as an example to promote brevity, clarity and ease of understandingand that embodiments of the invention are not limited to a particulartype, brand, or number of media devices and/or their components.

FIG. 3 illustrates a method for dynamic phase detection according to oneembodiment. Method 300 may be performed by processing logic that maycomprise hardware (e.g., circuitry, dedicated logic, programmable logic,microcode, etc.), software (such as instructions run on a processingdevice), or a combination thereof, such as firmware or functionalcircuitry within hardware devices. In one embodiment, method 300 isperformed by dynamic phase detection mechanism 110 of FIG. 1.

Method 300 starts at block 305 where an image from a number and type ofinput images is selected for selection of the best phase to representthe image. At block 310, a first calculation is performed to determinestability optimization with regard to each phase of the image by testingvarious pixel points on consecutive frames of each phase of the selectedimage. At block 315, a second calculation is performed to determinesharpness optimization.

At block 320, image consistency evaluation and suitability evaluationsare performed. In one embodiment, image consistency and suitabilityevaluation are independent of stability and sharpness optimizations,while consistency and suitability evaluations may determine whether APDoptimization is valid and applicable at a higher system level. If animage is determined to be inconsistent or unsuitable, any APDoptimization results may be ignored. At 325, in one embodiment, usingthe aforementioned calculations for determining stability, sharpness,consistency evaluation, and suitability evaluation, the best phase isselected. It is contemplated that the selected image may not necessarilybe the best at each of the stability or sharpness, but it may be fromthe best neighborhood of all images where certain compromises may bemade to some of the factors, such as stability over sharpness or viceversa, etc. At block 330, the image is transmitted to be viewed by usersvia a display device. The display device (e.g., display screen) may becoupled to or be part of a sink device (e.g., television, computingdevice) to display the image based on the best phase. In one embodiment,the selected best phase represents a phase the provides or displays theimage in the best possible manner that has strong jitter tolerance andis in accordance with the already-known human vision perceptions so theuser may appreciate and enjoy the image at the highest level and in anatural manner.

FIG. 5 illustrates components of a network computer device 505 employingdynamic phase detection mechanism 110 of FIG. 1 according to oneembodiment. In this illustration, a network device 505 may be any devicein a network, including, but not limited to, a computing device, anetwork computing system, a television, a cable set-top box, a radio, aBlu-ray player, a DVD player, a CD player, an amplifier, an audio/videoreceiver, a smartphone, a Personal Digital Assistant (PGA), a storageunit, a game console, or other media device. In some embodiments, thenetwork device 505 includes a network unit 510 to provide networkfunctions. The network functions include, but are not limited to, thegeneration, transfer, storage, and reception of media content streams.The network unit 510 may be implemented as a single system on a chip(SoC) or as multiple components.

In some embodiments, the network unit 510 includes a processor for theprocessing of data. The processing of data may include the generation ofmedia data streams, the manipulation of media data streams in transferor storage, and the decrypting and decoding of media data streams forusage. The network device may also include memory to support networkoperations, such as Dynamic Random Access Memory (DRAM) 520 or othersimilar memory and flash memory 525 or other nonvolatile memory. Networkdevice 505 also may include a read only memory (ROM) and or other staticstorage device for storing static information and instructions used byprocessor 515.

A data storage device, such as a magnetic disk or optical disc and itscorresponding drive, may also be coupled to network device 505 forstoring information and instructions. Network device 505 may also becoupled to an input/output (I/O) bus via an I/O interface. A pluralityof I/O devices may be coupled to I/O bus, including a display device, aninput device (e.g., an alphanumeric input device and or a cursor controldevice). Network device 505 may include or be coupled to a communicationdevice for accessing other computers (servers or clients) via externaldata network. The communication device may comprise a modem, a networkinterface card, or other well-known interface device, such as those usedfor coupling to Ethernet, token ring, or other types of networks.

Network device 505 may also include a transmitter 530 and/or a receiver540 for transmission of data on the network or the reception of datafrom the network, respectively, via one or more network interfaces 555.Network Device 505 may be the same as the communication media device 100of FIG. 1 employing phase mechanism 110 of FIG. 1. The transmitter 530or receiver 540 may be connected to a wired transmission cable,including, for example, an Ethernet cable 550, a coaxial cable, or to awireless unit. The transmitter 530 or receiver 540 may be coupled withone or more lines, such as lines 535 for data transmission and lines 545for data reception, to the network unit 510 for data transfer andcontrol signals. Additional connections may also be present. The networkdevice 505 also may include numerous components for media operation ofthe device, which are not illustrated here.

Network device 505 may be interconnected in a client/server networksystem or a communication media network (such as satellite or cablebroadcasting). A network may include a communication network, atelecommunication network, a Local Area Network (LAN), Wide Area Network(WAN), Metropolitan Area Network (MAN), a Personal Area Network (PAN),an intranet, the Internet, etc. It is contemplated that there may be anynumber of devices connected via the network. A device may transfer datastreams, such as streaming media data, to other devices in the networksystem via a number of standard and non-standard protocols.

In the description above, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present invention. It will be apparent, however, toone skilled in the art that the present invention may be practicedwithout some of these specific details. In other instances, well-knownstructures and devices are shown in block diagram form. There may beintermediate structure between illustrated components. The componentsdescribed or illustrated herein may have additional inputs or outputswhich are not illustrated or described.

Various embodiments of the present invention may include variousprocesses. These processes may be performed by hardware components ormay be embodied in computer program or machine-executable instructions,which may be used to cause a general-purpose or special-purposeprocessor or logic circuits programmed with the instructions to performthe processes. Alternatively, the processes may be performed by acombination of hardware and software.

One or more modules, components, or elements described throughout thisdocument, such as the ones shown within or associated with an embodimentof a DRAM enhancement mechanism may include hardware, software, and/or acombination thereof. In a case where a module includes software, thesoftware data, instructions, and/or configuration may be provided via anarticle of manufacture by a machine/electronic device/hardware. Anarticle of manufacture may include a machine accessible/readable mediumhaving content to provide instructions, data, etc.

Portions of various embodiments of the present invention may be providedas a computer program product, which may include a computer-readablemedium having stored thereon computer program instructions, which may beused to program a computer (or other electronic devices) to perform aprocess according to the embodiments of the present invention. Themachine-readable medium may include, but is not limited to, floppydiskettes, optical disks, compact disk read-only memory (CD-ROM), andmagneto-optical disks, read-only memory (ROM), random access memory(RAM), erasable programmable read-only memory (EPROM), EEPROM, magnet oroptical cards, flash memory, or other type of media/machine-readablemedium suitable for storing electronic instructions. Moreover, thepresent invention may also be downloaded as a computer program product,wherein the program may be transferred from a remote computer to arequesting computer.

Many of the methods are described in their most basic form, butprocesses can be added to or deleted from any of the methods andinformation can be added or subtracted from any of the describedmessages without departing from the basic scope of the presentinvention. It will be apparent to those skilled in the art that manyfurther modifications and adaptations can be made. The particularembodiments are not provided to limit the invention but to illustrateit. The scope of the embodiments of the present invention is not to bedetermined by the specific examples provided above but only by theclaims below.

If it is said that an element “A” is coupled to or with element “B,”element A may be directly coupled to element B or be indirectly coupledthrough, for example, element C. When the specification or claims statethat a component, feature, structure, process, or characteristic A“causes” a component, feature, structure, process, or characteristic B,it means that “A” is at least a partial cause of “B” but that there mayalso be at least one other component, feature, structure, process, orcharacteristic that assists in causing “B.” If the specificationindicates that a component, feature, structure, process, orcharacteristic “may”, “might”, or “could” be included, that particularcomponent, feature, structure, process, or characteristic is notrequired to be included. If the specification or claim refers to “a” or“an” element, this does not mean there is only one of the describedelements.

An embodiment is an implementation or example of the present invention.Reference in the specification to “an embodiment,” “one embodiment,”“some embodiments,” or “other embodiments” means that a particularfeature, structure, or characteristic described in connection with theembodiments is included in at least some embodiments, but notnecessarily all embodiments. The various appearances of “an embodiment,”“one embodiment,” or “some embodiments” are not necessarily allreferring to the same embodiments. It should be appreciated that in theforegoing description of exemplary embodiments of the present invention,various features are sometimes grouped together in a single embodiment,figure, or description thereof for the purpose of streamlining thedisclosure and aiding in the understanding of one or more of the variousinventive aspects. This method of disclosure, however, is not to beinterpreted as reflecting an intention that the claimed inventionrequires more features than are expressly recited in each claim. Rather,as the following claims reflect, inventive aspects lie in less than allfeatures of a single foregoing disclosed embodiment. Thus, the claimsare hereby expressly incorporated into this description, with each claimstanding on its own as a separate embodiment of this invention.

What is claimed is:
 1. An apparatus comprising: a first logic togenerate a first stability optimization of an image of a media streamacross two or more consecutive image frames at a first clock phase andto generate a second stability optimization across the two or moreconsecutive image frames at a second clock phase; and a second logic toselect a phase from between at least the first clock phase and thesecond clock phase based on the first stability optimization and thesecond stability optimization, wherein the selected clock phasefacilitates analog to digital conversion of the media stream.
 2. Theapparatus of claim 1, further comprising: a third logic to generate afirst sharpness optimization of the image at the first clock phase and asecond sharpness optimization of the image at the second clock phase,wherein the second logic selects the phase between at least the firstclock phase and the second clock phase further based on the firstsharpness optimization and the second sharpness optimization.
 3. Theapparatus of claim 2, wherein the third logic generates the firstsharpness optimization and the second sharpness optimization based onhigh frequency component energy of the image.
 4. The apparatus of claim1, further comprising: a third logic to evaluate image consistency ofthe image by calculating as sum of pixels values of the image; and afourth logic to evaluate image suitability of the image by examiningedge intensiveness of the image.
 5. The apparatus of claim 1, whereinthe second logic further scans and selects the image from a plurality ofimages in the media stream, wherein the selected image represents anideal image to be analyzed for selection between at least the firstclock phase and the second clock phase based on predetermined criteria.6. The apparatus of claim 1, wherein the first logic generates the firststability optimization and the second stability optimization from arandomly selected subset of pixels in the image.
 7. A method comprising:generating, at a media device, a first stability optimization of animage of a media stream across two or more consecutive image frames at afirst clock phase and a second stability optimization across the two ormore consecutive image frames at a second clock phase; and selecting aphase from between at least the first clock phase and the second clockphase based on the first stability optimization and the second stabilityoptimization, wherein the selected clock phase facilitates analog todigital conversion of the media stream.
 8. The method of claim 7,further comprising generating a first sharpness optimization of theimage at the first clock phase and a second sharpness optimization ofthe image at the second clock phase, wherein selecting the phase betweenat least the first clock phase and the second clock phase is furtherbased on the first sharpness optimization and the second sharpnessoptimization.
 9. The method of claim 8, wherein the first sharpnessoptimization and the second sharpness optimization are generated basedon high frequency component energy of the image.
 10. The method of claim7, further comprising scanning and selecting the image from a pluralityof images in the media stream, wherein the selected image represents anideal image to be analyzed for selection between at least the firstclock phase and the second clock phase based on predetermined criteria.11. The method of claim 7, further comprising: evaluating imageconsistency of the image by calculating as sum of pixels values of theimage; and evaluating image suitability of the image by examining edgeintensiveness of the image.
 12. The method of claim 7, wherein the firststability optimization and the second stability optimization aregenerated from a randomly selected subset of pixels in the image.
 13. Anapparatus comprising: a first logic to generate a first sharpnessoptimization of an image of a media stream at a first clock phase and asecond sharpness optimization of the image at a second clock phase,wherein each sharpness optimization is generated based on high frequencycomponent energy of the image; and a second logic to select a phase frombetween at least the first clock phase and the second clock phase basedon the first sharpness optimization and the second sharpnessoptimization, wherein the selected clock phase facilitates analog todigital conversion of the media stream.
 14. The apparatus of claim 13,further comprising: a third logic to generate a first stabilityoptimization of the image across two or more consecutive image frames atthe first clock phase and to generate a second stability optimizationacross the two or more consecutive image frames at the second clockphase, wherein the second logic selects the phase between at least thefirst clock phase and the second clock phase further based on the firststability optimization and the second stability optimization.
 15. Theapparatus of claim 14, wherein the third logic generates the firststability optimization and the second stability optimization from arandomly selected subset of pixels in the image.
 16. The apparatus ofclaim 13, further comprising: a third logic to evaluate imageconsistency of the image by calculating as sum of pixels values of theimage; and a fourth logic to evaluate image suitability of the image byexamining edge intensiveness of the image.
 17. A method comprising:generating, at a media device, a first sharpness optimization of animage of a media stream at a first clock phase and a second sharpnessoptimization of the image at a second clock phase, wherein eachsharpness optimization is generated based on high frequency componentenergy of the image; and selecting a phase from between at least thefirst clock phase and the second clock phase based on the firstsharpness optimization and the second sharpness optimization, whereinthe selected clock phase facilitates analog to digital conversion of themedia stream.
 18. The method of claim 17, further comprising generatinga first stability optimization of the image across two or moreconsecutive image frames at the first clock phase and a second stabilityoptimization across the two or more consecutive image frames at thesecond clock phase, wherein selecting the phase between at least thefirst clock phase and the second clock phase is further based on thefirst stability optimization and the second stability optimization. 19.The method of claim 18, wherein the first stability optimization and thesecond stability optimization are generated from a randomly selectedsubset of pixels in the image.
 20. The method of claim 17, furthercomprising: evaluating image consistency of the image by calculating assum of pixels values of the image; and evaluating image suitability ofthe image by examining edge intensiveness of the image.